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GLM 4.7 Flash vs GPT-5

Updated October 21, 2026. 43 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.7 Flash Replace GPT-5
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
5
GPT-5OpenAI
Coding
38.8
Overall
23.0
Output $/M
$10.00
38
vs boards won of 43 shared

Decision reading

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding.

GLM 4.7 Flash has the edge where output tokens cost 25.0x less, and where what matters is τ²-Bench Telecom or Design Arena: websites, where it leads.

Model AGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5OpenAI38.8/1003 independent benchmarks$0.39 per solved task
Shared results
43
GLM 4.7 Flash only
0
GPT-5 only
66
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GLM 4.7 Flash not benchmarked, GPT-5 38.8 from 3 benchmarks.
Widest category
Reasoning, 17.1 points apart on average over 6 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.7 Flash 41.7% against GPT-5 78.2%, 36.5 points apart on a 0 to 100 scale.
Output price
GLM 4.7 Flash $0.40 against GPT-5 $10.00 per million output tokens, 25.0x apart.
Context window
GLM 4.7 Flash takes 200K tokens, GPT-5 400K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGLM 4.7 FlashBarsGPT-5Ties
Coding03
Intelligence01
Agentic work10
Reasoning06
Math03
Knowledge04
Web design43
General018
All shared boards538
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
Aider polyglotNot measured88.0%Only GPT-5 measured
SWE-bench VerifiedNot measured74.4%Only GPT-5 measured
LMArena WebDevNot measured1418Only GPT-5 measured
AA Coding IndexNot measured37.8Only GPT-5 measured
LiveCodeBench (Vals AI)Not measured85.9%Only GPT-5 measured
SWE-bench Verified (Vals AI)Not measured69.0%Only GPT-5 measured
Vibe Code Bench (Vals AI)Not measured20.1%Only GPT-5 measured
LiveCodeBench (Artificial Analysis run)Not measured84.6%Only GPT-5 measured
Terminal-Bench Hard (Artificial Analysis run)22.0%37.9%GPT-5
Terminal-BenchNot measured49.6%Only GPT-5 measured
GSO-BenchNot measured6.9%Only GPT-5 measured
WeirdMLNot measured60.7%Only GPT-5 measured
ALE-BenchNot measured807.6Only GPT-5 measured
LMArena Text: coding13821436GPT-5
LMArena Text: software and IT13891420GPT-5
LMArena WebDev: HTMLNot measured1427Only GPT-5 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
AA Intelligence Index14.923.0GPT-5
Epoch Capabilities IndexNot measured150.0Only GPT-5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
τ²-Bench Telecom98.8%86.5%GLM 4.7 Flash
METR time horizonsNot measured69.6%Only GPT-5 measured
Remote Labor IndexNot measured1.7%Only GPT-5 measured
GDPvalNot measured34.8%Only GPT-5 measured
BALROGNot measured32.8%Only GPT-5 measured
DeepResearch BenchNot measured49.6%Only GPT-5 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
GPQA DiamondNot measured85.6%Only GPT-5 measured
MMMU Pro (Vals AI)Not measured81.5%Only GPT-5 measured
GPQA Diamond (Artificial Analysis run)58.1%85.4%GPT-5
Humanity's Last Exam (Artificial Analysis run)7.6%28.5%GPT-5
GPQA Diamond (Epoch AI run)60.5%86.2%GPT-5
ARC-AGINot measured65.7%Only GPT-5 measured
ARC-AGI-2Not measured9.9%Only GPT-5 measured
SimpleBenchNot measured56.7%Only GPT-5 measured
Chess puzzlesNot measured36.0%Only GPT-5 measured
Mystery game puzzlesNot measured23.0%Only GPT-5 measured
EBR-benchNot measured12.7%Only GPT-5 measured
VPCTNot measured66.0%Only GPT-5 measured
LMArena Text: hard prompts13561415GPT-5
LMArena Text: expert13571419GPT-5
LMArena Text: hard prompts in English13691419GPT-5
LMArena Vision: diagramsNot measured1252Only GPT-5 measured
LMArena Vision: homeworkNot measured1278Only GPT-5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
AIMENot measured93.4%Only GPT-5 measured
MATH 500 (Vals AI)Not measured96.0%Only GPT-5 measured
MGSM (Vals AI)Not measured92.8%Only GPT-5 measured
AA Math IndexNot measured94.3Only GPT-5 measured
AIME 2025 (Artificial Analysis run)Not measured94.3%Only GPT-5 measured
OTIS Mock AIME58.3%91.4%GPT-5
FrontierMath, tiers 1 to 3Not measured55.4%Only GPT-5 measured
FrontierMath, tier 4Not measured22.0%Only GPT-5 measured
ProofBenchNot measured18.0%Only GPT-5 measured
MATH level 5Not measured98.1%Only GPT-5 measured
LMArena Text: math13551407GPT-5
LMArena Text: mathematical work13691405GPT-5
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
MMLU ProNot measured86.5%Only GPT-5 measured
LegalBench (Vals AI)Not measured86.0%Only GPT-5 measured
CaseLaw (Vals AI)Not measured66.5%Only GPT-5 measured
CorpFin (Vals AI)Not measured61.1%Only GPT-5 measured
TaxEval (Vals AI)Not measured73.4%Only GPT-5 measured
MortgageTax (Vals AI)Not measured65.5%Only GPT-5 measured
MedQA (Vals AI)Not measured96.3%Only GPT-5 measured
MedCode (Vals AI)Not measured49.6%Only GPT-5 measured
MMLU Pro (Artificial Analysis run)Not measured87.1%Only GPT-5 measured
SimpleQA VerifiedNot measured50.1%Only GPT-5 measured
GeoBenchNot measured81.0%Only GPT-5 measured
LMArena Text: science13581416GPT-5
LMArena Text: medicine and healthcare13431413GPT-5
LMArena Text: legal and government13571431GPT-5
LMArena Text: business and finance13431400GPT-5
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index43
Web design benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
Design Arena: websites11941185GLM 4.7 Flash
Design Arena: UI components12081180GLM 4.7 Flash
Design Arena: game dev11351185GPT-5
Design Arena: data viz11231221GPT-5
Design Arena: 3D11211056GLM 4.7 Flash
Design Arena: all code categories11781168GLM 4.7 Flash
Design Arena: SVG10381189GPT-5
Design Arena: ASCII artNot measured1140Only GPT-5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index018
General benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
SAGE (Vals AI)Not measured43.7%Only GPT-5 measured
MedScribe (Vals AI)Not measured83.7%Only GPT-5 measured
IFBench60.8%73.1%GPT-5
Long context reasoning (AA-LCR)41.7%78.2%GPT-5
DTBenchNot measured90.7%Only GPT-5 measured
LMCANot measured40.0%Only GPT-5 measured
Fiction.LiveBenchNot measured97.2%Only GPT-5 measured
Creative writing (Lech Mazur)Not measured86.0%Only GPT-5 measured
LMArena Text13511406GPT-5
LMArena Text: instruction following13271388GPT-5
LMArena Text: creative writing12961365GPT-5
LMArena VisionNot measured1232Only GPT-5 measured
LMArena Text: English13731409GPT-5
LMArena Text: non-English13301397GPT-5
LMArena Text: Chinese14031422GPT-5
LMArena Text: German13361416GPT-5
LMArena Text: JapaneseNot measured1409Only GPT-5 measured
LMArena Text: Korean12831360GPT-5
LMArena Text: French13321409GPT-5
LMArena Text: Spanish13501399GPT-5
LMArena Text: Russian13331407GPT-5
LMArena Text: Polish12911431GPT-5
LMArena Text: multi-turn13421426GPT-5
LMArena Text: longer queries13451399GPT-5
LMArena Text: writing and language13201384GPT-5
LMArena Text: entertainment and media13041379GPT-5
LMArena Vision: EnglishNot measured1231Only GPT-5 measured
LMArena Vision: ChineseNot measured1267Only GPT-5 measured
LMArena Vision: reading textNot measured1246Only GPT-5 measured
LMArena Vision: humorNot measured1219Only GPT-5 measured
LMArena Vision: captioningNot measured1212Only GPT-5 measured
LMArena Vision: recognizing thingsNot measured1263Only GPT-5 measured
LMArena Vision: creative writingNot measured1210Only GPT-5 measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 Flash and GPT-5
BenchmarkGLM 4.7 FlashGPT-5Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GLM 4.7 Flash$0.0003Fits in one request
GPT-5$0.0063Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

GLM 4.7 Flash$0.0045Fits in one request
GPT-5$0.092Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 4.7 Flash$0.017Exceeds the context window
GPT-5$0.350Fits in one request

GLM 4.7 Flash costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GLM 4.7 Flash and GPT-5
SpecificationZ.ai GLM 4.7 FlashOpenAI GPT-5
MakerZ.aiOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJanuary 19, 2026August 7, 2025
Context window200K400K
Input $/Mtok$0.0653$1.25
Output $/Mtok$0.40$10.00
Coding indexNot benchmarked38.8
Independent measurements behind it03
Cost per solved taskNot computable$0.39
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 Flash better than GPT-5 for coding?

Only GPT-5 has a coding score, 38.8 on the Vibe Coding Index; GLM 4.7 Flash has none, so the two cannot be ranked on coding. GLM 4.7 Flash has the edge where output tokens cost 25.0x less, and where what matters is τ²-Bench Telecom or Design Arena: websites, where it leads.

Which is cheaper, GLM 4.7 Flash or GPT-5?

GLM 4.7 Flash costs $0.0653 per million input tokens and $0.40 per million output tokens; GPT-5 costs $1.25 and $10.00. Cost per solved task is known for GPT-5 only.

Which has the bigger context window, GLM 4.7 Flash or GPT-5?

GPT-5, with 400K tokens against 200K.

How many benchmarks is the GLM 4.7 Flash vs GPT-5 comparison based on?

43 benchmarks have a result for both models as of October 21, 2026. GLM 4.7 Flash's coding index rests on 0 independent benchmarks and GPT-5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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